Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.

Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.

Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.

Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance.     

Overestimation of self-reported driving exposure: Results from the SHRP2 Naturalistic Driving Study

Objectives: The accuracy of self-reported driving exposure has questioned the validity of using self-reported mileage to inform research questions. Studies examining the accuracy of self-reported driving exposure compared to objective measures find low validity, with drivers overestimating and underestimating driving distance. The aims of the current study were to (1) examine the discrepancy between self-reported annual mileage and driving exposure the following year and (2) investigate whether these differences depended on age and annual mileage.

Methods: Two estimates of drivers’ self-reported annual mileage collected during vehicle installation (obtained via prestudy questionnaires) and approximated annual mileage driven (based upon Global Positioning System data) were acquired from 3,323 participants who participated in the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study.

Results: A Wilcoxon signed rank test showed that there was a significant difference between self-reported and annual driving exposure during participation in SHRP 2, with the majority of self-reported responses overestimating annual mileage the following year, irrespective of whether an ordinal or ratio variable was examined. Over 15% of participants provided self-reported responses with over 100% deviation, which were exclusive to participants underestimating annual mileage. Further, deviations in reporting differed between participants who had low, medium, and high exposure, as well as between participants in different age groups.

Conclusions: These findings indicate that although self-reported annual mileage is heavily relied on for research, such estimates of driving distance may be an overestimate of current or future mileage and can influence the validity of prior research that has utilized estimates of driving exposure.     

Environmental life cycle assessment of different types of the municipal wastewater pipeline network

With the onset of social life, humans have considered waste disposal as essential, and they have been able to repel it through brick and clay channels. Checking sewage pipes for energy consumption and a longer lifetime than other sewage system components is important. Climate change and exploitation of industrial resources have made environmental impacts, which are important factors in decision making. The purpose of this study was to introduce the most suitable type of sewage pipe considering environmental protection. Therefore, we applied the environmental life cycle assessment (LCA) method, using Sima Pro 8.2.3 software for the one-kilometer length of concrete pipes (300 mm in diameter), Polyvinyl chloride (PVC), and polyethylene (PE) (315 mm in diameter). Also, the BEES method and sensitivity analysis were used to validate the results. The comparison between three types of municipal wastewater pipes indicated that PE pipes are a more environmentally friendly option than PVC, and concrete pipes in pipe recycling, reducing extraction from untapped resources, and inefficient extraction of resources. Electricity, diesel fuel, and sulfate resistance cement consumption for concrete production are the most pollution elements in the LCA of concrete pipes. Usage of PVC granular, sanitary landfill of PVC pipes, and using hydraulic drill in LCA of PVC pipes are the most elements of generating pollution. The usage of PE granules, PE pipes landfilling, hydraulic excavator, and electricity consumption in the LCA of the PE pipes are the greatest polluting parameters.     

Sulfur cycle as an electron mediator between carbon and nitrate in a constructed wetland microcosm

• Fe(III) accepted the most electrons from organics, followed by NO₃^‒, SO₄^2‒, and O₂. • The electrons accepted by SO₄^2‒ could be stored in the solid AVS, FeS₂-S, and S⁰. • The autotrophic denitrification driven by solid S had two-phase characteristics. • A conceptual model involving electron acceptance, storage, and donation was built. • S cycle transferred electrons between organics and NO₃^‒ with an efficiency of 15%. A constructed wetland microcosm was employed to investigate the sulfur cycle-mediated electron transfer between carbon and nitrate. Sulfate accepted electrons from organics at the average rate of 0.84 mol/(m³·d) through sulfate reduction, which accounted for 20.0% of the electron input rate. The remainder of the electrons derived from organics were accepted by dissolved oxygen (2.6%), nitrate (26.8%), and iron(III) (39.9%). The sulfide produced from sulfate reduction was transformed into acid-volatile sulfide, pyrite, and elemental sulfur, which were deposited in the substratum, storing electrons in the microcosm at the average rate of 0.52 mol/(m³·d). In the presence of nitrate, the acid-volatile and elemental sulfur were oxidized to sulfate, donating electrons at the average rate of 0.14 mol/(m³·d) and driving autotrophic denitrification at the average rate of 0.30 g N/(m³·d). The overall electron transfer efficiency of the sulfur cycle for autotrophic denitrification was 15.3%. A mass balance assessment indicated that approximately 50% of the input sulfur was discharged from the microcosm, and the remainder was removed through deposition (49%) and plant uptake (1%). Dominant sulfate-reducing (i.e., Desulfovirga, Desulforhopalus, Desulfatitalea, and Desulfatirhabdium) and sulfur-oxidizing bacteria (i.e., Thiohalobacter, Thiobacillus, Sulfuritalea, and Sulfurisoma), which jointly fulfilled a sustainable sulfur cycle, were identified. These results improved understanding of electron transfers among carbon, nitrogen, and sulfur cycles in constructed wetlands, and are of engineering significance.     

How farmers develop local ecological knowledge for on-farm tree management: The perspectives of some farming communities of Ghana

Scientific insights into what it means to manage on-farm trees by local farmers, is an essential step towards documenting local ecological knowledge for sustainable landscape management. A study was therefore conducted in the Kumawu Forest District in the Ashanti Region of Ghana to assess how farmers conceptualise on-farm tree management and develop local knowledge for it. Using a case study approach, data were collected through informal interviews and focus group discussions with 120 farmers drawn from 15 communities who were involved in the management of three cropping systems; cocoa, maize and cassava-cocoyam-plantain mix. It was observed that the farmers regard on-farm tree management as a continuous process which occurs in three phases of the farming cycle; land preparation, crop cultivation and fallow management. For each of the three phases, farmers are guided by specific principles that ensure enough light penetration in-between tree crowns in the land preparation phase, suitable spacing between trees and crops in the crop cultivation phase and adequate tree regeneration in the fallow phase. The decisions made during the selection of tree species, spacing of trees adjudged suitable for any particular cropping system and recruitment of saplings prior to the fallow phase of farming constitute tree management. Farmers develop tree management knowledge by studying the physical characteristics of species, matching them to ecological functions they could perform and how they are likely to respond to treatments meant to control or enhance their development. Species are then subjected to trial and recommended or otherwise.     

基于情感思维的安全管理模式研究

为促进安全管理，提高效率与效果，对基于情感思维的安全管理进行研究，将情感思维融于安全管理，基于情感思维的定义、内涵及功能，具体分析安全管理中情感思维的功能及其功能综合作用，建立安全管理中情感思维功能作用理论模型；根据该理论模型分析情感思维驱动力及强化作用及其对安全目标实现的影响；建立基于情感思维的安全管理设计模式，最后提出优化安全管理的措施与方法，以促进安全管理的实施。研究表明:基于情感思维的安全管理研究，能较好地体现安全管理人本原理，发挥情感的能动作用，将理性融入其中与情感进行平衡，实现安全管理的优化。     

A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

Identification of aggressive driving from naturalistic data in car-following situations

Introduction: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. Method: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. Results: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.     

Are older drivers’ driving patterns during an on-road driving task representative of their real-world driving patterns?

Abstract

Objective: The current study investigated whether older drivers’ driving patterns during a customized on-road driving task were representative of their real-world driving patterns.

Methods: Two hundred and eight participants (male: 68.80%; mean age?=?81.52 years, SD?=?3.37 years, range?=?76.00–96.00 years) completed a customized on-road driving task that commenced from their home and was conducted in their own vehicle. Participants’ real-world driving patterns for the preceding 4-month period were also collected via an in-car recording device (ICRD) that was installed in each participant’s vehicle.

Results: During the 4-month period prior to completing the on-road driving task, participants’ median real-world driving trip distance was 2.66?km (interquartile range [IQR]?=?1.14–5.79?km) and their median on-road driving task trip distance was 4.41?km (IQR?=?2.83–6.35?km). Most participants’ on-road driving task trip distances were classified as representative of their real-world driving trip distances (95.2%, n?=?198).

Conclusions: These findings suggest that most older drivers were able to devise a driving route that was representative of their real-world driving trip distance. Future research will examine whether additional aspects of the on-road driving task (e.g., average speed, proportion of trips in different speed zones) are representative of participants’ real-world driving patterns.